同济大学学报（自然科学版）2024，Vol.52Issue(6)：838-845,855,9.DOI:10.11908/j.issn.0253-374x.24139
考虑人机信任匹配的人机协同控制策略
Human-machine Cooperative Control Strategy Considering Human-machine Trust Matching
摘要
Abstract
The level of human-machine mutual trust is a key factor affecting the performance of human-machine cooperative systems.This paper presents a Stackelberg Game-based cooperative control strategy that considers human-machine trust matching.Firstly,a method was proposed for assessing the mutual trust level between drivers and machines.Based on this,the weight allocation in cooperative driving was performed according to the level of human-machine trust matching.Subsequently,a model predictive control framework was adopted,and the optimal cooperative control strategy was obtained by combining the Stackelberg Game theory for optimization.Finally,driver-in-the-loop experiments were conducted to validate the proposed cooperative control strategy.Results demonstrate that,for drivers with different trust matching levels,the strategy can improve the precision of path tracking by 70.91％,and reduce the driving burden by 44.03％.The proposed strategy enhances the driving performance and reduces the driver workload.关键词
人机协同控制/人机信任匹配/权重分配/主从博弈Key words
human-machine cooperative control/human-machine trust matching/weight allocation/Stackelberg Game分类
交通工程引用本文复制引用
孙剑,阳友康,岳李圣飒,韩嘉懿,王子衿,尹恒..考虑人机信任匹配的人机协同控制策略[J].同济大学学报（自然科学版）,2024,52(6):838-845,855,9.基金项目
国家自然科学基金(52125208) （52125208）
上海市软科学项目(23692123300) （23692123300）
